Abstract: Descriptive data relating to at least a subset of a plurality of entities on a website is retrieved over a network. Endorsement data relating to the plurality of entities is retrieved from the website. A first set of probabilities is determined reflecting a probability that endorsements can be attributed to specific aspects. A second set of probabilities is determined reflecting a probability that terms can be attributed to aspects. Using the first set of probabilities and the second set of probabilities, a subset of the terms that are most probably associated with each entity are selected. Tags are then generated for each entity using the selected terms.

Abstract: Descriptive data relating to at least a subset of a plurality of entities on a website is retrieved over a network. Endorsement data relating to the plurality of entities is retrieved from the website. A first set of probabilities is determined reflecting a probability that endorsements can be attributed to specific aspects. A second set of probabilities is determined reflecting a probability that terms can be attributed to aspects. Using the first set of probabilities and the second set of probabilities, a subset of the terms that are most probably associated with each entity are selected. Tags are then generated for each entity using the selected terms.

Abstract: Descriptive data relating to at least a subset of a plurality of entities on a website is retrieved over a network. Endorsement data relating to the plurality of entities is retrieved from the website. A first set of probabilities is determined reflecting a probability that endorsements can be attributed to specific aspects. A second set of probabilities is determined reflecting a probability that terms can be attributed to aspects. Using the first set of probabilities and the second set of probabilities, a subset of the terms that are most probably associated with each entity are selected. Tags are then generated for each entity using the selected terms.

Abstract: Methods and apparatus for determining aspects of locations based on interactions of users with the locations. In some implementations, an aspect of a location may be determined based on comparing a first interaction measure for the location to a second measure. The first interaction measure may be determined based on a first group of interactions that are associated with the location. In some implementations, the second measure may be determined based on a second group of interactions that include additional interactions that are in addition to the interactions of the first group.

Abstract: The subject matter disclosed herein relates to generating an abstract of an electronic document based at least in part on a utility metric associated with a group phrases as well as on a ranked order of sentences.

Abstract: Descriptive data relating to at least a subset of a plurality of entities on a website is retrieved over a network. Endorsement data relating to the plurality of entities is retrieved from the website. A first set of probabilities is determined reflecting a probability that endorsements can be attributed to specific aspects. A second set of probabilities is determined reflecting a probability that terms can be attributed to aspects. Using the first set of probabilities and the second set of probabilities, a subset of the terms that are most probably associated with each entity are selected. Tags are then generated for each entity using the selected terms.

Abstract: Descriptive data relating to at least a subset of a plurality of entities on a website is retrieved over a network. Endorsement data relating to the plurality of entities is retrieved from the website. A first set of probabilities is determined reflecting a probability that endorsements can be attributed to specific aspects. A second set of probabilities is determined reflecting a probability that terms can be attributed to aspects. Using the first set of probabilities and the second set of probabilities, a subset of the terms that are most probably associated with each entity are selected. Tags are then generated for each entity using the selected terms.

Abstract: Disclosed are apparatus and methods for compressing a set of numerical values for a set of feature values, which can be utilized by a rule based or decision tree system. In certain embodiments, the numerical values are transformed into a subset of integer values based on how they are to be analyzed by conditional processes of the rule based or decision tree system that compare such numerical values to one or more threshold values. This transformation is accomplished such that if the rule based or decision tree system is applied after transformation, identical results are produced as compared to the original numerical values being used by the rule based or decision tree system. Other compression techniques may also be applied to the transformed values. An altered rule based or decision tree system, in which threshold values are also transformed to integer values, may be applied to the transformed values. Alternatively, the rule based or decision tree system may be applied to a set of decoded numerical values.

Abstract: Method, system, and programs for computing similarity. Input data is first received from one or more data sources and then analyzed to obtain an input feature vector that characterizes the input data. An index is then generated based on the input feature vector and is used to archive the input data, where the value of the index is computed based on an improved Johnson-Lindenstrass transformation (FJLT) process. With the improved FJLT process, first, the sign of each feature in the input feature vector is randomly flipped to obtain a flipped vector. A Hadamard transformation is then applied to the flipped vector to obtain a transformed vector. An inner product between the transformed vector and a sparse vector is then computed to obtain a base vector, based on which the value of the index is determined.

Abstract: Method, system, and programs for computing similarity. Input data is first received from one or more data sources and then analyzed to obtain an input feature vector that characterizes the input data. An index is then generated based on the input feature vector and is used to archive the input data, where the value of the index is computed based on an improved Johnson-Lindenstrass transformation (FJLT) process. With the improved FJLT process, first, the sign of each feature in the input feature vector is randomly flipped to obtain a flipped vector. A Hadamard transformation is then applied to the flipped vector to obtain a transformed vector. An inner product between the transformed vector and a sparse vector is then computed to obtain a base vector, based on which the value of the index is determined.

Abstract: Descriptive data relating to at least a subset of a plurality of entities on a website is retrieved over a network. Endorsement data relating to the plurality of entities is retrieved from the website. A first set of probabilities is determined reflecting a probability that endorsements can be attributed to specific aspects. A second set of probabilities is determined reflecting a probability that terms can be attributed to aspects. Using the first set of probabilities and the second set of probabilities, a subset of the terms that are most probably associated with each entity are selected. Tags are then generated for each entity using the selected terms.

Abstract: A geographic region is automatically determined for an Internet resource based on information that has been gathered over time through the automatic monitoring of certain “click” activities of Internet search engine-using users. Over time, the search engine collects information for each click. Using this click-related data, the search engine estimates the geographic region with which the resource ought to be associated. The fact that a significant proportion of clicks on a resource's hyperlink are clicks that “came through” a search engine portal that is associated with a geographic region tends to suggest that the resource ought to be associated with that geographic region. Similarly, the fact that a significant proportion of clicks on a resource's hyperlink are clicks that were made by users whose computers have IP addresses that are associated with a geographic region tends to suggest that the resource ought to be associated with that geographic region.

Abstract: The subject matter disclosed herein relates to generating an abstract of an electronic document based at least in part on a utility metric associated with a group phrases as well as on a ranked order of sentences.

Abstract: Disclosed are apparatus and methods for compressing a set of numerical values for a set of feature values, which can be utilized by a rule based or decision tree system. In certain embodiments, the numerical values are transformed into a subset of integer values based on how they are to be analyzed by conditional processes of the rule based or decision tree system that compare such numerical values to one or more threshold values. This transformation is accomplished such that if the rule based or decision tree system is applied after transformation, identical results are produced as compared to the original numerical values being used by the rule based or decision tree system. Other compression techniques may also be applied to the transformed values. An altered rule based or decision tree system, in which threshold values are also transformed to integer values, may be applied to the transformed values. Alternatively, the rule based or decision tree system may be applied to a set of decoded numerical values.

Abstract: Disclosed are apparatus and methods for providing linking abstracts for a plurality of search results. In certain embodiments, an abstract of a listed search result is revised to include links to locations within the associated search result document that are proximate to one or more abstract portions. When the user selects a particular linkable abstract portion within a particular listed search result, the user is then provided with the corresponding location within the particular search result document. That is, the linked abstract portion is caused to be presented to the user.